Latest Episodes

The divide between Python 2 and 3 lasted a long time, and in recent years all of the new features were added to version 3. To help bridge the gap and extend the viability of version 2 Naftali Harris created Tauthon, a fork of Python 2 that backports features from Python 3. In this episode he explains his motivation for creating it, the process of maintaining it and backporting features, and the ways that it is being used by developers who are unable to make the leap. This was...

Dependency management in Python has taken a long and winding path, which has led to the current dominance of Pip. One of the remaining shortcomings is the lack of a robust mechanism for resolving the package and version constraints that are necessary to produce a working system. Thankfully, the Python Software Foundation has funded an effort to upgrade the dependency resolution algorithm and user experience of Pip. In this episode the engineers working on these improvements, Pradyun Gedam, Tzu-Ping Chung, and Paul Moore, discuss the history of Pip, the...

One of the most common causes of bugs is incorrect data being passed throughout your program. Pydantic is a library that provides runtime checking and validation of the information that you rely on in your code. In this episode Samuel Colvin explains why he created it, the interesting and useful ways that it can be used, and how to integrate it into your own projects. If you are tired of unhelpful errors due to bad data then listen now and try it out today.

More of us are working remotely than ever before, many with no prior experience with a remote work environment. In this episode Quinn Slack discusses his thoughts and experience of running Sourcegraph as a fully distributed company. He covers the lessons that he has learned in moving from partially to fully remote, the practices that have worked well in managing a distributed workforce, and the challenges that he has faced in the process. If you are struggling with your remote work situation then this conversation has some useful tips...

After you write your application, you need a way to make it available to your users. These days, that usually means deploying it to a cloud provider, whether that's a virtual server, a serverless platform, or a Kubernetes cluster. To manage the increasingly dynamic and flexible options for running software in production, we have turned to building infrastructure as code. Pulumi is an open source framework that lets you use your favorite language to build scalable and maintainable systems out of cloud infrastructure. In this episode Luke Hoban, CTO...

Python has become a major player in the machine learning industry, with a variety of widely used frameworks. In addition to the technical resources that make it easy to build powerful models, there is also a sizable library of educational resources to help you get up to speed. Sebastian Raschka's contribution of the Python Machine Learning book has come to be widely regarded as one of the best references for newcomers to the field. In this episode he shares his experiences as an author, his views on why Python...

Python has an embarrasment of riches when it comes to web frameworks, each with their own particular strengths. FastAPI is a new entrant that has been quickly gaining popularity as a performant and easy to use toolchain for building RESTful web services. In this episode Sebastián Ramirez shares the story of the frustrations that led him to create a new framework, how he put in the extra effort to make the developer experience as smooth and painless as possible, and how he embraces extensability with lightweight dependency injection and...

Distributed computing is a powerful tool for increasing the speed and performance of your applications, but it is also a complex and difficult undertaking. While performing research for his PhD, Robert Nishihara ran up against this reality. Rather than cobbling together another single purpose system, he built what ultimately became Ray to make scaling Python projects to multiple cores and across machines easy. In this episode he explains how Ray allows you to scale your code easily, how to use it in your own projects, and his ambitions to...

Bioinformatics is a complex and computationally demanding domain. The intuitive syntax of Python and extensive set of libraries make it a great language for bioinformatics projects, but it is hampered by the need for computational efficiency. Ariya Shajii created the Seq language to bridge the divide between the performance of languages like C and C++ and the ecosystem of Python with built-in support for commonly used genomics algorithms. In this episode he describes his motivation for creating a new language, how it is implemented, and how it is being...

The state of the art in natural language processing is a constantly moving target. With the rise of deep learning, previously cutting edge techniques have given way to robust language models. Through it all the team at Explosion AI have built a strong presence with the trifecta of SpaCy, Thinc, and Prodigy to support fast and flexible data labeling to feed deep learning models and performant and scalable text processing. In this episode founder and open source author Matthew Honnibal shares his experience growing a business around cutting edge...